Background: Fatigue significantly affects health-related quality of life (HRQoL) in patients with immune thrombocytopenia (ITP). However, the interplay between fatigue and cytokines in ITP remains poorly understood. Methods: This study included 100 patients with persistent or chronic ITP who had not received ITP-directed therapy in the previous 8 weeks and 50 age-matched healthy controls. Fatigue and HRQoL were assessed using the Functional Assessment of the Chronic Illness Therapy (FACIT) scale. Concurrently, plasma levels of interleukin (IL)-2, IL-4, IL-6, IL-10, IL-12, IL-17, and interferon-gamma (IFN-γ) were measured via enzyme-linked immunosorbent assay (ELISA). Results: ITP patients had significantly lower total FACIT scores [median 146 (range 59–160]) and fatigue subscale scores [median 45 (range 9–52]) than controls [155 (149–159) and 49 (44–52), respectively; both p < 0.001]. IL-12 levels were significantly elevated in patients (313.2 vs. 95.5 pg/mL; p < 0.001) and showed a significant negative correlation with FACIT scores (Spearman’s ρ = –0.272, p = 0.007). Multivariate analysis revealed that female sex, longer disease duration among patients with chronic ITP (> 24 months), and elevated IL-12 levels were independently associated with greater fatigue and poorer HRQoL. Conclusions ITP is associated with significant fatigue and HRQoL impairment, with IL-12 emerging as a potential immunological marker linked to this symptom burden.

OBJECTIVES: Prompt detection is a cornerstone in the control and prevention of infectious diseases. The Integrated Disease Surveillance Project of India identifies outbreaks, but it does not exactly predict outbreaks. This study was conducted to assess temporal correlation between Google Trends and Integrated Disease Surveillance Programme (IDSP) data and to determine the feasibility of using Google Trends for the prediction of outbreaks or epidemics. METHODS: The Google search queries related to malaria, dengue fever, chikungunya, and enteric fever for Chandigarh union territory and Haryana state of India in 2016 were extracted and compared with presumptive form data of the IDSP. Spearman correlation and scatter plots were used to depict the statistical relationship between the two datasets. Time trend plots were constructed to assess the correlation between Google search trends and disease notification under the IDSP RESULTS: Temporal correlation was observed between the IDSP reporting and Google search trends. Time series analysis of the Google Trends showed strong correlation with the IDSP data with a lag of −2 to −3 weeks for chikungunya and dengue fever in Chandigarh (r > 0.80) and Haryana (r > 0.70). Malaria and enteric fever showed a lag period of −2 to −3 weeks with moderate correlation. CONCLUSIONS: Similar results were obtained when applying the results of previous studies to specific diseases, and it is considered that many other diseases should be studied at the national and sub-national levels.
Communicable Diseases ; Dataset ; Dengue ; Disease Notification ; Disease Outbreaks* ; Epidemiological Monitoring ; India* ; Malaria ; Public Health Surveillance ; Typhoid Fever